In today’s fast-paced and interconnected world, mental health is more important than ever. The constant pressures of work, social media, and global events can take a toll on our emotional and ...
The challenge lies in generating effective agentic workflows for Large Language Models (LLMs). Despite their remarkable capabilities across diverse tasks, creating workflows that combine multiple LLMs ...
Zyphra has officially released Zamba2-7B, a state-of-the-art small language model that promises unprecedented performance in the 7B parameter range. This model outperforms existing competitors, ...
The problem with efficiently linearizing large language models (LLMs) is multifaceted. The quadratic attention mechanism in traditional Transformer-based LLMs, while powerful, is computationally ...
Language models (LMs) are widely utilized across domains like mathematics, coding, and reasoning to handle complex tasks. These models rely on deep learning techniques to generate high-quality outputs ...
XAI, or Explainable AI, brings about a paradigm shift in neural networks that emphasizes the need to explain the decision-making processes of neural networks, which are well-known black boxes. In XAI, ...
A Model Inversion (MI) attack is a type of privacy attack on machine learning and deep learning models, where an attacker tries to invert the model’s outputs to recreate privacy-sensitive training ...
Predibase announces the Predibase Inference Engine, their new infrastructure offering designed to be the best platform for serving fine-tuned small language models (SLMs). The Predibase Inference ...
Large language models (LLMs) often fail to consistently and accurately perform multi-step reasoning, especially in complex tasks like mathematical problem-solving and code generation. Despite recent ...
Retrieval-augmented generation (RAG) has become a key technique in enhancing the capabilities of LLMs by incorporating external knowledge into their outputs. RAG methods enable LLMs to access ...
Large language models (LLMs) have greatly advanced various natural language processing (NLP) tasks, but they often suffer from factual inaccuracies, particularly in complex reasoning scenarios ...
LLMs leverage the transformer architecture, particularly the self-attention mechanism, for high performance in natural language processing tasks. However, as these models increase in depth, many ...